bi: how can your high-performance bi system meet expectations when you feed it 85 octane data
DESCRIPTION
Many BI projects fail, some because of data issues. Using Data Governance and associated skills such as Master Data Management and Data Stewardship can help improve your information and projects.TRANSCRIPT
BI: How Can Your High-Performance BI System Meet Expectations When You
Feed It 85 Octane Data
Making Data Quality Part of the Data Life CycleRay McGlew [email protected]
Brought to You By:
BI Failure Reasons
Gartner: 70%-80% BI Projects Fail• Lack of Business Support and Ownership• Poor Quality Data• Lack of Requirements• Scope Creep• Funding• Big-Bang Approach
Life Cycle of Data
• Creation (usually transactions)• Operational Use• Analytical Use• Destruction
Who “Owns” The Data?
• IT responsible for conserving it– Restrict use according to rules– Providing access– Keeping it safe
• Business responsible for managing it– Create rules for IT to use– Providing IT with requirements for access
• Bottom line… it is a Corporate Resource
Data Concerns
• Privacy – Credit Cards– Health Records
• Security• Accuracy• Usability• Availability
Regulatory Compliance
• Privacy regulations• Legal limits on how long you can keep certain
data• Providing lineage on data used for reporting– Sarbanes Oxley– SEC filings
Quality Data
• Easiest to clean at the source• Some methods to “clean” data– Standardize– Validate
• Data Cleansing Tools
Data Cleansing
Data Governance
“Data governance (DG) refers to the overall management of the availability, usability, integrity, and security of the data employed in an enterprise. “
Data Governance Facets
• Data Stewardship• Data Dictionary/Glossary• Master Data Management• Strong Management Promotion
Data Stewardship
• Splits responsibility for ensuring great data• Business– Defines what important data elements are– Defines the rules for acquiring data– Looks for cross-organizational uses
• IT– Responsible for technical methods– Acquires and maintains tools
Data Dictionary
• Platform for spreading the knowledge• Is used in conjunction with reporting tools• The more data knowledge is used, the better it
gets• Can be started using in-house tools• Starting point for Master Data Management
Master Data Management
• Data Governance should drive MDM• Technology – Facilitates– NOT the driver
Strong Management Promotion
• Cross-functional at the highest level of the organization
• Will require funding• Must break through “It will cost my
department to improve the data quality so their department can save time “
Data Governance and Lifecycle
• Data Creation– Standard values– Validation at the source
• Operational use– Required for some customers and vendors
• Analytical use– Easier to integrate across systems and groups
• Destruction
Data Governance is NOT a Program!
• Culture Change• Integrated with other activities– Business Intelligence– Business Process Re-engineering– ERP Implementation– Mergers
Data Governance Tips
• Prioritize– Based on business value– Based on Pain– Low Hanging Fruit
• Don’t try to boil the ocean!
Resources
DAMA International (www.dama.org)Enterprise Data World
DAMA Philadelphia (www.dama-phila.org)Data Governance (www.datagovernance.com)Data Governance Professionals Org (www.dgpo.org)
Love your data, and stay the course, for it will be with you long after flashy apps are gone.